2000/05/08 by Patrik Simons, Simons, Patrik · 2 citations
Computer Science · #AI-based Problem Solving and Planning #Artificial Intelligence (cs.AI) #F.4.1 #FOS: Computer and information sciences #I.2.3 #I.2.8 #Logic in Computer Science (cs.LO) #Logic, Reasoning, and Knowledge #Semantic Web and Ontologies #cs.AI #cs.LO
paper · pdf · doi:10.48550/arxiv.cs/0005010
109 pages, 30 figures, dissertation for the degree of Doctor of Technology
arxiv created 2000/05/08 · openalex publication_date 2000/05/08 · arxiv updated 2009/11/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
An algorithm for computing the stable model semantics of logic programs is developed. It is shown that one can extend the semantics and the algorithm to handle new and more expressive types of rules. Emphasis is placed on the use of efficient implementation techniques. In particular, an implementation of lookahead that safely avoids testing every literal for failure and that makes the use of lookahead feasible is presented. In addition, a good heuristic is derived from the principle that the search space should be minimized. Due to the lack of competitive algorithms and implementations for the computation of stable models, the system is compared with three satisfiability solvers. This shows that the heuristic can be improved by breaking ties, but leaves open the question of how to break them. It also demonstrates that the more expressive rules of the stable model semantics make the semantics clearly preferable over propositional logic when a problem has a more compact logic program representation. Conjunctive normal form representations are never more compact than logic program ones.